On-Device ML Engineer — Edge AI & LiteRT

Google

Town of Montana (WI)

On-site

USD 147,000 - 210,000

Full time

12 days ago
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Job summary

Google is seeking a Software Engineer for On-Device Machine Learning in Sunnyvale, CA. You will join a team building LiteRT, Google's on-device AI framework, enabling acceleration across edge devices and a range of platforms from mobile to embedded.

The role emphasizes collaboration, design reviews, and contributions to model optimization, data processing, and on-device deployment across GPUs, Pixel TPUs, NPUs, and CPUs. A strong background in ML frameworks and mobile development is preferred.

Qualifications

  • Bachelor's degree or equivalent practical experience.
  • 2 years of software development experience or 1 year with an advanced degree.
  • 2 years of ML infrastructure experience (model deployment/evaluation/processing).
  • Experience with runtimes and performance tuning.
  • Experience in mobile development.

Responsibilities

  • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies.
  • Implement solutions in ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.
  • Develop LiteRT, Google's on-device AI framework for first- and third-party use with hardware acceleration.
  • Enable on-device deployment of models across accelerators (GPU/TPU/NPUs/CPU) on Android, Chrome, iOS, desktop, etc.
  • Improve performance of on-device model inference via runtime and kernel optimizations.

Skills

Mobile development
ML deployment
Performance tuning
Software development
ML infrastructure

Education

Bachelor's degree or equivalent
Master's degree in CS or related

Tools

TensorFlow
PyTorch
JAX

Job description

Google is seeking a Software Engineer for On-Device Machine Learning in Sunnyvale, CA. You will join a team building LiteRT, Google's on-device AI framework, enabling acceleration across edge devices and a range of platforms from mobile to embedded.

The role emphasizes collaboration, design reviews, and contributions to model optimization, data processing, and on-device deployment across GPUs, Pixel TPUs, NPUs, and CPUs. A strong background in ML frameworks and mobile development is preferred.

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Bonus target
Equity
Benefits